Our Research and Modelling Platform
The Drawdown Research & Modelling platform provides an open source platform for developing, deploying and executing Climate Solution models to any context, region or scale. The Python-based software kernel is collectively build and maintained by the Drawdown Global Research Collaborative. It's free to use by anyone.
The Drawdown Data and Models are the core of the platform. The modelling effort includes the Drawdown Models themselves, and an open source repository containing the datasets on which the Models are built. Collaboration and communication tools wrap around the modelling effort; for anyone to join, communicate and collaborate on new and existing projects. Intuitive Graphical User Interfaces (GUI’s) enable users to interact with the data based on the unique needs of their role — steward, contributor, or user.
Full solution model customization
The software enables users and contributors to edit existing or develop new methods and propose new solutions. This includes adding new solutions, adjusting solutions’ rankings or reordering them based on new data, improving and enriching models and better measuring and mapping progress towards drawdown.
Equipped with decision support tools
The platform’s tools enable users to tailor existing information and input new or specific data to create scenario’s that support decision making. It assists users running ‘what-if scenarios’ and helps localizing global data to deliver information within any desired boundaries, e.g. at national, regional, or local scales and across value chains.
Intuitive and graphical interfaces
Interfaces enable users to interact with data based on their unique needs as steward, contributor, or end-user: assisting in accessing and understanding the information they’re looking for in a way that feels intuitive and non-intimidating. For example, selecting more inputs and adding specificity or creating custom scenarios.
Real time data integration
The modelling engine has the capacity to integrate data from external sources, such as greenhouse gas emissions sensors and satellite data. For example, technologies are being developed that can collect real-time information on current greenhouse gas emissions, GPS mapping of biomass cover, and soil sensors measuring organic soil carbon in terrestrial biomass: enabling regional models to provide real-time feedback on the success of those solutions as they are implemented.
Data Commons Architecture
A (semi) open data structure allows to share and store data fully open, privately or shared with only a specific community. Standard technologies enable incorporation of any new data source and Digital Object Identifiers (DOI’s) make citing easy.
Incorporated expanded impact metrics
Data beyond greenhouse gas emissions and financial costs and savings will be incorporated so that users will be able to evaluate data in relationship to evaluate data in relationship to additional metrics such as earth feedbacks, policy and financial mechanisms, human health and well-being, technological developments, educational initiatives, economic indicators (such as jobs), biodiversity indicators, ecosystem services, and environmental health.
Build of what already exists
Developed and updated over time
All in check
All components of our models are freely available on Gitlab.
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Become a beta user
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